Bayesian network analysis of factors influencing type 2 diabetes, coronary heart disease, and their comorbidities.

OBJECTIVE: Bayesian network (BN) models were developed to explore the specific relationships between influencing factors and type 2 diabetes mellitus (T2DM), coronary heart disease (CAD), and their comorbidities. The aim was to predict disease occurrence and diagnose etiology using these models, thereby informing the development of effective prevention and control strategies for T2DM, CAD, and their comorbidities. METHOD: Employing a case-control design, the study compared individuals with T2DM, CAD, and their comorbidities (case group) with healthy counterparts (control group). Univariate and multivariate Logistic regression analyses were conducted to identify disease-influencing factors. The BN structure was learned using the Tabu search algorithm, with parameter estimation achieved through maximum likelihood estimation. The predictive performance of the BN model was assessed using the confusion matrix, and Netica software was utilized for visual prediction and diagnosis. RESULT: The study involved 3,824 participants, including 1,175 controls, 1,163 T2DM cases, 982 CAD cases, and 504 comorbidity cases. The BN model unveiled factors directly and indirectly impacting T2DM, such as age, region, education level, and family history (FH). Variables like exercise, LDL-C, TC, fruit, and sweet food intake exhibited direct effects, while smoking, alcohol consumption, occupation, heart rate, HDL-C, meat, and staple food intake had indirect effects. Similarly, for CAD, factors with direct and indirect effects included age, smoking, SBP, exercise, meat, and fruit intake, while sleeping time and heart rate showed direct effects. Regarding T2DM and CAD comorbidities, age, FBG, SBP, fruit, and sweet intake demonstrated both direct and indirect effects, whereas exercise and HDL-C exhibited direct effects, and region, education level, DBP, and TC showed indirect effects. CONCLUSION: The BN model constructed using the Tabu search algorithm showcased robust predictive performance, reliability, and applicability in forecasting disease probabilities for T2DM, CAD, and their comorbidities. These findings offer valuable insights for enhancing prevention and control strategies and exploring the application of BN in predicting and diagnosing chronic diseases.

High-flux and bright betatron X-ray source generated from femtosecond laser pulse interaction with sub-critical density plasma.

Recent progress on betatron X-ray source enables the exploration of new physics in fundamental science; however, the application range is still limited by the source flux and brightness. In this Letter, we show the generation of more than 1 × 1012 photons (energy > 1 keV) with a peak brightness of 7.8 × 1022 photons/(s mm2 mrad2) at 0.1% bandwidth (BW) at 10 keV, driven by a femtosecond laser pulse of ≈5.5 J and a sub-critical density plasma (SCDP). The source flux is more than two orders of magnitude higher than that from typical laser wakefield electron acceleration. This method to produce high-flux and bright X-ray source would open a wide range of applications.

Upregulation of miR-181a impairs lipid metabolism by targeting PPARα expression in nonalcoholic fatty liver disease.

Recent studies have reported elevated expression of miR-181a in patients with non-alcoholic fatty liver disease (NAFLD), suggesting that it may play an important role in liver lipid metabolism and insulin resistance. We aimed to investigate the effect of miR-181a in lipid metabolism and find new treatments for NAFLD. The expression level of miR-181a in NAFLD patient serum and a palmitic acid (PA)-induced NAFLD cell model was examined by Q-PCR. Oil red O staining and triglyceride assays were used to assess lipid accumulation in hepatocytes. Western blotting was used to detect the protein expression levels of peroxisome proliferator-activated receptor-α (PPARα) and the fatty acid ß-oxidation-related genes. Direct interactions were validated by dual-luciferase reporter gene assays. MiR-181a expression was significantly upregulated in the serum of NAFLD patients and PA-induced hepatocytes. Inhibition of miR-181a expression resulted in the increased expression of PPARα and its downstream genes, and PA-induced lipid accumulation in hepatocytes was also inhibited. Upregulation of miR-181a resulted in the downregulation of its direct target PPARα and downstream gene expression of PPARα as well as aggravated lipid accumulation in hepatocytes. At the same time, the increased expression of PPARα can offset lipid accumulation in hepatocytes induced by miR-181a mimics. This study demonstrates that reducing the expression of miR-181a may improve lipid metabolism in NAFLD. The downregulation of miR-181a expression can be a therapeutic strategy for NAFLD by modulating its target PPARα.

Associations between dietary inflammatory index and stroke risk: based on NHANES 2005-2018.

The dietary inflammatory index (DII) is a measure of the inflammatory potential of the diet and is closely associated with insulin resistance (IR) and stroke. And IR may play an important role in the development of stroke. Therefore, this study aimed to evaluate the relationship between DII and stroke risk while delving into the potential role of IR in this association. We analyzed data from the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018, performing weighted univariate analyses, logistic regression, and mediation analyses. At baseline, 3.89% of participants developed stroke, and we observed stroke patients exhibited higher DII scores. After adjusting for covariates, compared to participants in the first quartile of DII scores, those in the third quartile and fourth quartile had increased odds of experiencing a stroke (OR: 1.78, 95% CI: 1.18-2.68) and (OR: 1.70, 95% CI: 1.16-2.50), respectively. Moreover, a significant dose-response relationship was observed (P-trend < 0.05). However, there was no observed interaction between DII and homeostatic model assessment-IR (HOMA-IR) concerning stroke risk, and HOMA-IR did not mediate the association between DII and stroke. In summary, our study elucidated the significant association between DII and stroke risk, independent of IR. This insight suggests that an anti-inflammatory diet may serve as an effective strategy for stroke prevention.

The association between dietary inflammation index and depression.

Objective: We aimed to evaluate whether depression is associated with increased risk of dietary inflammatory index (DII) or energy-adjusted DII (E-DII) and whether the association is partly explained by insulin resistance (IR). Methods: Base on the National Health and Nutrition Examination Survey (NHANES) 2005-2018. Univariate analyses of continuous and categorical variables were performed using t-test, ANOVA, and χ 2 test, respectively. Logistic regression was used to analyze the relationship between DII or E-DII and depression in three different models. Mediation analysis was used to assess the potential mediation effects of homeostatic model assessment-IR (HOMA-IR). Results: A total of 70,190 participants were included, and the DII score was higher in the depressed group. DII score was related to all participant characteristics except age (p < 0.05). After being included in covariates (Model 3), participants in the highest quartile of DII score have increased odds of depression (OR: 1.82, 95% CI: 1.28-2.58) compared with those in the first quartile of DII score. And, a significant dose-response relationship was found (p-trend <0.05). No interaction between DII and HOMA-IR was observed in terms of the risk of depression, and HOMA-IR did not find to play a mediating role in the association between DII and depression. Similar results were obtained for the association between E-DII and depression. Conclusion: Our results suggest that a higher pro-inflammatory diet increases the risk of depression in U.S. adults, while there was no evidence of a multiplicative effect of DII or E-DII and HOMA-IR on disease risk, nor of a mediating effect of HOMA-IR.

Genetically predicted lifestyle factors, socioeconomic status and risk of coronary artery disease in individuals with diabetes: a Mendelian randomization study.

Background: This study explores the causal links between genetically predicted lifestyle factors, socioeconomic status, and coronary artery disease (CAD) risk in individuals with diabetes using a bidirectional Mendelian-randomization approach. Methods: This study explored the potential causal relationships of lifestyle factors and socioeconomic status with the risk of CAD in diabetes patients by a bidirectional, two-sample Mendelian-randomization (MR) analysis. Results: Genetically predicted smoking initiation (p = 0.005, 95% CI: 1.08-1.55) and insomnia (p = 0.001, 95% CI: 1.06-1.29) were associated with a higher risk of CAD in individuals with diabetes, whereas educational attainment (p = 0.0001, 95% CI: 0.47-0.78) was associated with a lower risk of CAD. The lifetime smoking index (p = 0.016, 95% CI: 1.12-3.03) was suggestively associated with a higher risk of CAD, while household income before taxes (p = 0.048, 95% CI: 0.41-1.00) was suggestively associated with a lower risk of CAD. In addition, we observed a suggestive negative association between the genetically predicted risk of CAD and the lifetime smoking index (p = 0.016, 95% CI: 0.98-0.99) and a significant causal relationship between the risk of CAD and household income before taxes (p = 0.006, 95% CI: 0.97-0.99). Conclusion: The results of this study provide evidence that smoking initiation, lifetime smoking index and insomnia are associated with an increased risk of CAD in individuals with diabetes, educational attainment and household income before taxes are associated with a reduced risk of CAD in individuals with diabetes, and the possible role of lifetime smoking index and household income before taxes on the risk of CAD in individuals with diabetes. It provides an opportunity for the prevention and management of CAD in individuals with diabetes.

Association between systemic immune-inflammatory index and diabetes mellitus: mediation analysis involving obesity indicators in the NHANES.

Background: Inflammation and obesity have been widely recognized to play a key role in Diabetes mellitus (DM), and there exists a complex interplay between them. We aimed to clarify the relationship between inflammation and DM, as well as the mediating role of obesity in the relationship. Methods: Based on the National Health and Nutrition Examination Survey (NHANES) 2005-2018. Univariate analyses of continuous and categorical variables were performed using t-test, linear regression, and χ2 test, respectively. Logistic regression was used to analyze the relationship between Systemic Immune-Inflammatory Index (SII) or natural logarithm (Ln)-SII and DM in three different models. Mediation analysis was used to determine whether four obesity indicators, including body mass index (BMI), waist circumference (WC), visceral adiposity index (VAI) and lipid accumulation product index (LAP), mediated the relationship between SII and DM. Results: A total of 9,301 participants were included, and the levels of SII and obesity indicators (BMI, WC, LAP, and VAI) were higher in individuals with DM (p < 0.001). In all three models, SII and Ln-SII demonstrated a positive correlation with the risk of DM and a significant dose-response relationship was found (p-trend <0.05). Furthermore, BMI and WC were associated with SII and the risk of DM in all three models (p < 0.001). Mediation analysis showed that BMI and WC mediated the relationship between SII with DM, as well as Ln-SII and DM, with respective mediation proportions of 9.34% and 12.14% for SII and 10.23% and 13.67% for Ln-SII (p < 0.001). Conclusion: Our findings suggest that increased SII levels were associated with a higher risk of DM, and BMI and WC played a critical mediating role in the relationship between SII and DM.

ATL I, Acts as a SIRT6 Activator to Alleviate Hepatic Steatosis in Mice via Suppression of NLRP3 Inflammasome Formation.

Accumulating evidence has highlighted that sirtuin-6 (SIRT6) plays an important role in hepatic gluconeogenesis and lipogenesis. We aim to investigate the underlying mechanisms and pharmacological interventions of SIRT6 on hepatic steatosis treatment. Herein, our results showed that atractylenolide I (ATL I) activated the deacetylase activity of SIRT6 to promote peroxisome proliferator-activated receptor alpha (PPARα) transcription and translation, while suppressing nuclear factor NF-kappa-B (NFκB)-induced NACHT, LRR, and PYD domains containing protein 3 (NLRP3) inflammasome formation. Together, these decreased the infiltration of F4/80 and CD11B positive macrophages, accompanied by decreased mRNA expression and serum levels of tumor necrosis factor alpha (TNF-α), interleukin-6 (IL6), and interleukin-1 beta (IL1ß). Additionally, these changes decreased sterol regulatory element-binding protein-1c (SREBP-1c) expression, while restoring carnitine O-palmitoyltransferase 1a (Cpt1a) expression, to decrease the size of adipocytes and adipose deposition, which, in turn, reversed high-fat diet (HFD)-induced liver weight and body weight accumulation in C57 mice. SIRT6 knockout or hepatic SIRT6 knockout in C57 mice largely abolished the effect of ATL I on ameliorating hepatic steatosis. Taken together, our results suggest that ATL I acts as a promising compound that activates SIRT6/PPARα signaling and attenuates the NLRP3 inflammasome to ameliorate hepatic inflammation and steatosis.

How do socioeconomic factors influence urban PM2.5 pollution in China? Empirical analysis from the perspective of spatiotemporal disequilibrium.

PM2.5 pollution has harmed the health and social lives of residents, and although evidence of PM2.5 pollution caused by human activities has been reported in a large body of literature, traditional econometric and spatial models can explain the contribution of a given factor from only a global perspective. Given this limitation, this study quantitatively investigated the effects of the spatiotemporal heterogeneity of various socioeconomic factors on PM2.5 pollution in 273 Chinese cities from 2010 to 2016 by exploratory spatial data analysis (ESDA) and geographically weighted regression (GWR). The spatiotemporal distribution pattern and intrinsic driving mechanism of city-level PM2.5 pollution were systematically examined. The results indicate the following: (1) The cities with high PM2.5 pollution are located north of the Yangtze River and east of the Hu line. A notable positive spatial correlation was observed between these cities, and nearly one-third of the cities are in the HH clustering area. (2) From the global regression point of view, population size and economic development are the main factors causing the deterioration and spread of PM2.5 pollution in Chinese cities, and population size undoubtedly exerts the strongest influence. Industrial structure, economic development, openness degree, urbanization and road intensity also play weak roles in promoting urban PM2.5 pollution. (3) The socioeconomic factors influencing pollution exhibit significant spatial heterogeneity. Specifically, the cities in which pollution is promoted by economic development are mainly concentrated in the northeast and western regions. The cities in which population size exerts a positive driving effect are in most regions, except for a few central and western cities. Three targeted strategies for developing more sustainable cities are comprehensively discussed by building on the understanding of the socioeconomic driving mechanism for PM2.5 pollution.

Role of Noncoding RNA in Development of Nonalcoholic Fatty Liver Disease.

Nonalcoholic fatty liver disease (NAFLD) is increasing in prevalence globally, but little is known about its specific molecular mechanisms. During the past decade, noncoding RNAs (ncRNAs) have been linked to NAFLD initiation and progression. They are a class of RNAs that play an important role in regulating gene expression despite not encoding proteins. This review summarizes recent research on the relationship between ncRNAs and NAFLD. We discussed the potential applicability of ncRNAs as a biomarker for early NAFLD diagnosis and assessment of disease severity. With further study, ncRNAs should prove to be valuable new targets for NAFLD treatment and benefit the development of noninvasive diagnostic methods.